Concurrent Control Chart Pattern Recognition: A Systematic Review

The application of statistical methods to monitor a process is critical ensure its stability. Statistical control aims detect and identify abnormal patterns that disrupt the natural behaviour process. Most studies in literature are focused on recognising single patterns. However, many industrial processes, more than one unusual chart pattern may appear simultaneously, i.e., concurrent (CCP). Therefore, this paper present classification framework based categories systematically organise analyse existing regarding CCP recognition provide concise summary developments performed so far helpful guide for future research. search only included journal articles proceedings area. was conducted using Web Science Scopus databases. As result, 41 were considered proposed scheme. It consists designed assure an in-depth analysis most relevant topics research Results concluded lack field. main findings include use machine learning methods; study non-normally distributed processes; consideration different from shift, trend, cycle behaviours.